My research lies at the intersection of experimental mechanics, computational modeling, and materials engineering, with a particular emphasis on understanding the mechanical behavior of materials across multiple length scales. I employ high-resolution digital image correlation (HR-DIC) techniques to capture full-field strain measurements at the microstructural level, enabling direct observation of localized deformation and damage processes during mechanical loading. This experimental insight is essential for validating and calibrating advanced simulation tools. On the modeling side, I specialize in the crystal plasticity finite element method (CPFEM), which allows for the simulation of anisotropic plastic deformation in polycrystalline materials by incorporating crystallographic slip and grain-scale heterogeneity. Through CPFEM, I can investigate the influence of microstructure—such as grain orientation, size, and morphology—on the macroscopic response of materials under various loading conditions. A significant part of my work is devoted to materials produced by additive manufacturing (AM), particularly metal alloys fabricated using laser powder bed fusion. These materials often exhibit complex microstructures and process-induced defects, which strongly influence their mechanical performance. By integrating HR-DIC and CPFEM, I aim to better understand how the unique microstructural features of AM materials govern their deformation and failure mechanisms. This integrated approach aligns with the principles of Integrated Computational Materials Engineering (ICME), where experimental data, advanced modeling, and process–structure–property relationships are combined to accelerate materials development. Ultimately, my goal is to contribute to the predictive design and optimization of high-performance materials for structural applications, using a synergy of experimental validation and multiscale simulation.